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Cold Start problem

Instructor: Applied AI Course Duration: 6 mins

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Matrix Factorization for recommender systems: Netflix Prize Solution

Word vectors as MF

Recommender Systems and Matrix Factorization

1.1

Problem formulation: IMDB Movie reviews

23 min

1.2

Content based vs Collaborative Filtering

11 min

1.3

Similarity based Algorithms

16 min

1.4

Matrix Factorization: PCA, SVD

23 min

1.5

Matrix Factorization: NMF

3 min

1.6

Matrix Factorization for Collaborative filtering

23 min

1.7

Matrix Factorization for feature engineering

9 min

1.8

Clustering as MF

21 min

1.9

Matrix Factorization for recommender systems: Netflix Prize Solution

30 min

1.10

Cold Start problem

6 min

1.11

Word vectors as MF

20 min

1.12

15 min

1.13

11 min

1.14

Exercise: Word Vectors using Truncated SVD.

7 min